Evolving notes, images and sounds by Luis Apiolaza

Category: teaching (Page 3 of 14)

Fascinated by change

The last 2 months or so I have been revisiting the Chilean forest sector and mentally comparing values with other two places: Australia (where I worked 6 years) and New Zealand (where I’ve been living for close to two decades). Previous related posts here and here.

We often get stuck considering specific values of dynamic systems instead of the overall trends; a bit like worrying about a specific frame instead of the whole movie.

New Zealand radiata pine has been remarkable stable: around 89% of the planted forest estate area for a long time and with a fairly low percentage of eucalypts (under 2%). In contrast, Australia and Chile have experienced large changes on the percentage of eucalypts (mostly Eucalyptus globulus and E. nitens) versus radiata pine during the last 20 years. In Chile this change has been accompanied by capital investment in processing facilities.

At the same time, the Chilean curves hide a fundamental change during the last 10 years.

Participation of Eucalyptus spp on the total forest estate in hectares (left) and as a percentage (right).

We all stopped expanding our forest estate

A few days ago I was comparing afforestation figures—planting in area that didn’t have trees before—across New Zealand, Chile and Australia. There was a bit of discussion in the comments but, of course, that was only a small part of painting a picture of the plantation forestry sector in each country.

This time, I am plotting the total planted forest estate (excluding native forests) in each country. All three Southern Hemisphere countries have stopped expanding their total estate, with only a few years difference. New Zealand reached its peak area in 2003 (1.82 million ha), Australia in 2009 (2.02 million ha) and Chile in 2013 (2.45 million ha).

Leo Tolstoy wrote in Anna Karenina that “all happy families are alike; each unhappy family is unhappy in its own way”. All three forest sectors have different reasons to explain or justify the area contraction, although there is at least one commonality: uncertainty.

For example, the ETS mess in the early 2000s in NZ resulted in large areas of young plantations converted to dairy use in the Canterbury region. My previous post showed an uptick on newly planted land in New Zealand (some of it converted from meat production to forestry); still it is not big enough to compensate for the loss of planted land in previous years. Chile has experienced a decade-long megadrought, large forest fires in the 2016-17 season (a drop of area), together with political complexity from 2019 onwards.

All three countries are supposed to increase CO2 sequestration as part of their commitments against climate change. It is looking like a hard call to achieve this with our current political settings.

Area total de plantaciones forestales en Australia, Chile y Nueva Zelanda.

New plantations in AU, NZ and CL

Looking at new forest plantations areas in Chile (data from INFOR), Australia (ABARES) and New Zealand (MPI) since 1994, as the Chilean dataset starts then.

Interesting to see how the expansion of the forest estate collapsed in all three Southern Hemisphere countries at the start of the 2010s. Lately, New Zealand has seen an increase mostly due to market for Carbon Sequestration.

Why did I choose those three countries? I have worked in all of them and all three use radiata pine (although new plantings may involve Eucalyptus as well).

New planted areas (in hectares) of forest species in Australia, Chile and New Zealand.

Leaking genetic gain: not quite a selection index

A few years ago I was talking with a breeder who spent substantial time running genetic analyses, with fairly sophisticated linear mixed models. From there the breeder obtained BLUPs for a couple of selection criteria (using an animal model with heterogeneous site variances), heritabilities, genetic correlations, etc. The typical stuff.

Then came the leak: let’s say that the criteria were stem diameter (dbh) and wood basic density (den). The breeder thought that dbh was twice as important as den, therefore used a selection index weighing the breeding values as I = 2 * dbh + 1 * den. Easy.

My jaw dropped, because I couldn’t see how the breeder was accounting for the different genetic variances, the heritabilities, the genetic correlation or the relative economic importance of the criteria. I couldn’t because the breeder was not considering any of that.

The breeding programme used a “faux selection index”. At first sight it looked the part, but it completely wasted all the effort used in the genetic analyses. Why? Someone was trying to be clever and nobody else audited the methodology.

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